# Kashikoi: Simulation-based evaluation for AI agents

Canonical: https://thelazyweb.com/companies/kashikoi/
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Author: Ali Abouelatta (https://thelazyweb.com/authors/ali-abouelatta/)
Published: 2026-09-19
Updated: 2026-09-19
Research type: Company profile
Method: Company and accelerator sources checked 2026-09-19. Product claims are attributed to their sources; this is research, not a hands-on product trial.

Kashikoi is a simulation engine for benchmarking AI agents. It fits a team that wants to test an agent against customized, multi-turn scenarios and behavioral goals instead of trusting public benchmarks, hand-written prompts or a few happy-path traces.

## What it does

[Kashikoi’s current site](https://www.getkashikoi.com/) lets a team connect an agent, describe what it should do and run simulated interactions that produce metrics and actionable recommendations. The examples show security, data-analysis and code agents evaluated on accuracy, context understanding, severity, false positives and task-specific success.

The useful decision is whether the benchmark reflects the product’s actual values and users. Kashikoi’s [YC launch](https://www.ycombinator.com/launches/Nfa-kashikoi-simulation-engine-for-benchmarking-ai-agents) describes CPU-friendly world models that interview agents, generate diverse data and detect stale regression suites. The team says a customer can compare its agent with a competitor

[Kashikoi: Simulation-based evaluation for AI agents](<https://www.thelazyweb.com/companies/kashikoi/>)

Source observed: 2026-09-20T02:21:54.176Z. Last checked: 2026-10-08T01:56:08.846+00:00.

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